Research
Early Design Review of Boundary Scan To Enhancing Testability
Fatigue and Shear Properties of High Reliable Solder Joints
Liquid Dispensed Thermal Materials for High Volume Manufacturing
Effect of Process Changes and Flux on Mid-Chip Solder Balling
Effect of Fine Lead-Free Solder Powder on the Reflow Property Pastes
Embedded Fibers Enhance Nano-Scale Interconnections
Electronic Packages and Modules Based on Embedded Die Technologies
3D Printed Electronics for Printed Circuit Structures
MORE RESEARCH
Latest Industry News
Foxconn to Shift Some Apple Production to Vietnam
GM Opens Up a New Front in Its Battle With Tesla: Batteries
Chinese handset vendors keenly building up inventory
Apple suppliers' exodus from China won't slow down under Biden
Exposing Apple Mini M1 SoC
Taiwan PC monitor shipments to drop in 4Q20, says Digitimes Research
The Best Smartphones
Autonomous Vehicle Software Analyzes and Predicts Driving Events
MORE INDUSTRY NEWS

Leading the Intelligent Enterprise



Leading the Intelligent Enterprise
AI and machine learning offer ways to boost productivity, develop talent, and more, enhancing the ability to make decisions in complex situations.
Technology Briefing

Transcript


What does it take to transform a company into an AI-enabled “intelligent enterprise?” We’ll examine what companies have learned so far from their real-world efforts.

Artificial intelligence and machine learning offer new ways to boost productivity, develop talent, and drive organizational change by enhancing managers’ ability to make the right calls in complex situations.

Augmented intelligence tools have already made an impact on many companies, but the next revolution will happen when every aspect of a business, from top to bottom, is designed with AI in mind. This new construct is called an intelligent enterprise.

Like other major revolutions in management, it’s poised to transform industries and organizations for decades to come. As Joseph Byrum, a chief data scientist at financial services company Principal explained recently in MIT Sloan Management Review, leaders will need to harness machine intelligence for decision-making across the business, assemble the right talent, and recognize the benefits and limitations of AI to shape organizational strategy in order to prepare for this next phase.

It’s not hard to find examples of the amazing things we can do with artificial intelligence. AI and data analytics have changed the centuries-old techniques of plant breeding, helped advance cutting-edge research into disease, and even been used to decipher damaged ancient Greek tablets.

What these achievements have in common is that they are discrete, structured tasks. In each example, algorithms are used to absorb available data, recognize patterns therein, simulate outcomes, and select moves or produce results based on the statistical likelihood of success. In-plant breeding, for example, the simple step of designing a trial to see whether your breeding effort has succeeded or failed requires choosing from a set of 1.16 trillion possible combinations. Yet, increasing efficiency in this highly complex process through data analytics can save millions of dollars.

If improving one aspect of one process through data analytics can have a massive payoff, imagine what can happen when an organization takes advantage of AI’s ability to learn, analyze, and optimize across all processes and business functions.

That prompts us to ask “How Can AI Accelerate Leadership?

Businesses, particularly large corporations with a global footprint, are complex adaptive systems. No one person, or even one group of managers, can know what’s going on at all levels of an organization consisting of thousands of employees. Even so, the CEO is responsible for keeping the board and shareholders happy, positioning the company for the future, maintaining employee morale, and developing an advantage over the competition — all while turning a profit. Although the CEO relies on an executive team for support across these different functions, he or she ultimately shoulders the blame for bad choices. No wonder most CEOs at large-cap companies don’t last more than five years.

With so much responsibility, the CEO’s scarcest resource becomes time, and that’s where AI brings the most value to the top job. AI is an ideal tool for observing and gathering the available information touching on business operations. This includes internal reporting data as well as relevant external news stories and analysis relevant to the industry, digested and categorized by natural language processing algorithms. The Reuters news service, for example, uses AI to sift through 700 million daily tweets to spot breaking news that can be handed to a journalist for further investigation.

The intelligent enterprise must similarly process a mountain of data, prioritizing items according to relevance, which helps to avoid information overload for the leaders reviewing the reports. This gives the CEO maximum awareness of what’s happening throughout the business and the industry so that more of his or her time can be spent addressing issues likely to have an impact on the bottom line.

Moreover, the intelligent enterprise imagines AI systems in every division, department, unit, and group in the organization, including human resources, IT, marketing, finance, operations, and so on, so that each of these operations can be optimized with augmented intelligence systems that provide decision support to human employees.

Many HR departments already use a simple form of textual analytics — keyword scoring — to sort through unwieldy stacks of résumés that accumulate whenever a new job is posted. Applications for an accountant position that don’t mention, for example, the required academic credential or license can be tossed out right away. NASA’s AI system performs a deeper analysis that evaluates the context in which the keywords are used.

In the intelligent enterprise, more-advanced expert systems would use cognitive engines to understand the applications. Moreover, they would not focus narrowly on making the HR manager’s life easier. Each corporate unit’s and division’s systems would exchange information automatically, so the HR system would know when new talent might be needed. It could review past applications and have potential candidates lined up for consideration as soon as any new hiring was approved. In this way, the system would become a key component in advancing the CEO’s goals by ensuring that the company had the talent it needs to execute the overall mission.

The interconnection between business divisions would also give the CEO a real-time look into company performance. Data from each business unit wouldn’t be filtered by preconceived ideas about what the numbers ought to look like or shaded by department heads putting the best face on the results. The numbers would speak for themselves.

With a clear view of what’s happening, the CEO could swiftly reorient the company, as needed, to remedy problems or take advantage of favorable conditions. Armed with solid information and options weighed by AI simulations, the CEO could formulate multiple potential strategies to deal with the situations that arise. Instead of being based on hunches, emotions, or guesswork, these strategies would be fully informed by the best available data.

While innovation in AI systems continues to rapidly evolve, they are not all-knowing — in fact, artificial “general intelligence” exists only in science fiction. For now, it still falls to the human CEO and executive team to pick the strategy and execute it. But machines and AI systems are incredibly valuable for presenting data and providing options for leaders to consider based on different real-world contexts and goals. For example, sometimes the CEO will want to take a long-shot risk. Or perhaps it’s important to spend money on an initiative that won’t hit certain strategic targets but will improve employee morale. Reality is far too complex for a statistical algorithm to imagine every possibility that leaders might take into consideration.

Experienced CEOs are needed to consider the intangible factors a machine will miss. While the CEO’s primary job is making decisions, the role doesn’t end once a choice has been made. Here, AI tools are essential for monitoring results and evaluating whether the strategy is producing the intended effect. When bad choices are made, it’s important to change course quickly.

The continuous cycle of acting and reviewing results is critical for updating or abandoning strategies when necessary to achieve the organization’s goals.

Constant reevaluation of the company’s direction, in matters big and small, may seem like a waste of time, but it’s an effective insurance policy against complacency. Adaptability allows a business to stay ahead of customer and market needs and avoid becoming the next BlackBerry, Blockbuster, or Borders.

What AI does is enforce discipline on corporate strategies. It continuously, and automatically, evaluates questions like, “Is the plan working?” or “How good are the forecasts and projections?” It plots out alternatives — what happens if the company pivots in this direction or that direction? The intelligent enterprise also provides clarity about the goals and objectives of the organization, aligning every business division toward the overall strategy by setting goals (such as, by having the talent on hand to accomplish the next mission) and tracking progress toward those goals and the end results.

Sometimes overall change is needed, and sometimes it’s not. The intelligent enterprise is a system designed to be ready for either possibility. In a complex market environment, success comes to the companies best able to adapt to fast-changing circumstances. By building adaptability into the structure of the company, AI helps the CEO manage challenges as varied as the disruptions of a global pandemic or the discovery of new technologies.

Companies are investing in AI today, but to achieve the ultimate strategic goals of this investment, organizations must broaden their sights beyond creating augmented intelligence tools for limited tasks. In order to turn this broader vision into reality, leaders must prioritize assembling the right talent pipeline and technology infrastructure to enable the intelligent enterprise of tomorrow.

Comments

No comments have been submitted to date.

Submit A Comment


Comments are reviewed prior to posting. You must include your full name to have your comments posted. We will not post your email address.

Your Name


Your Company
Your E-mail


Your Country
Your Comments



Board Talk
Modify Rework Procedures for Assemblies Fabricated Using OSP?
What Causes Solder Icicles During Wave Soldering
Review of Tin-Copper and Tin-Nickel Intermetallic Thickness
Can High Particle Concentrations Impact PCB Assembly?
Trouble With Skewed DPAK Components
Moisture Barrier Bag Issues
How to Reduce Voiding on QFN Components
Can Mixing Wave Solder Pallets Cause Contamination?
MORE BOARD TALK
Ask the Experts
Reflow Oven Calibration Schedule
Insufficient Plated Hole Fill with Electrolytic Capacitors
Through Hole Connector Solder Joint Hole Fill
Selective Solder System Purchased At Auction
Out-gassing and Cleaning
Stencil Cleaning Procedure
Challenging Cleaning Problem
Selective Printing for BGA Components
MORE ASK THE EXPERTS